Python pandas.core.algorithms._hashtables() Examples

The following are 5 code examples of pandas.core.algorithms._hashtables(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas.core.algorithms , or try the search function .
Example #1
Source File: categorical.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _get_codes_for_values(values, categories):
    """
    utility routine to turn values into codes given the specified categories
    """
    from pandas.core.algorithms import _get_data_algo, _hashtables
    dtype_equal = is_dtype_equal(values.dtype, categories.dtype)

    if dtype_equal:
        # To prevent erroneous dtype coercion in _get_data_algo, retrieve
        # the underlying numpy array. gh-22702
        values = getattr(values, '_ndarray_values', values)
        categories = getattr(categories, '_ndarray_values', categories)
    elif (is_extension_array_dtype(categories.dtype) and
          is_object_dtype(values)):
        # Support inferring the correct extension dtype from an array of
        # scalar objects. e.g.
        # Categorical(array[Period, Period], categories=PeriodIndex(...))
        try:
            values = (
                categories.dtype.construct_array_type()._from_sequence(values)
            )
        except Exception:
            # but that may fail for any reason, so fall back to object
            values = ensure_object(values)
            categories = ensure_object(categories)
    else:
        values = ensure_object(values)
        categories = ensure_object(categories)

    (hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
    (_, _), cats = _get_data_algo(categories, _hashtables)
    t = hash_klass(len(cats))
    t.map_locations(cats)
    return coerce_indexer_dtype(t.lookup(vals), cats)
Example #2
Source File: categorical.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def _get_codes_for_values(values, categories):
    """
    utility routine to turn values into codes given the specified categories
    """

    from pandas.core.algorithms import _get_data_algo, _hashtables
    if not is_dtype_equal(values.dtype, categories.dtype):
        values = _ensure_object(values)
        categories = _ensure_object(categories)

    (hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
    (_, _), cats = _get_data_algo(categories, _hashtables)
    t = hash_klass(len(cats))
    t.map_locations(cats)
    return coerce_indexer_dtype(t.lookup(vals), cats)
Example #3
Source File: categorical.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _get_codes_for_values(values, categories):
    """
    utility routine to turn values into codes given the specified categories
    """
    from pandas.core.algorithms import _get_data_algo, _hashtables
    dtype_equal = is_dtype_equal(values.dtype, categories.dtype)

    if dtype_equal:
        # To prevent erroneous dtype coercion in _get_data_algo, retrieve
        # the underlying numpy array. gh-22702
        values = getattr(values, '_ndarray_values', values)
        categories = getattr(categories, '_ndarray_values', categories)
    elif (is_extension_array_dtype(categories.dtype) and
          is_object_dtype(values)):
        # Support inferring the correct extension dtype from an array of
        # scalar objects. e.g.
        # Categorical(array[Period, Period], categories=PeriodIndex(...))
        try:
            values = (
                categories.dtype.construct_array_type()._from_sequence(values)
            )
        except Exception:
            # but that may fail for any reason, so fall back to object
            values = ensure_object(values)
            categories = ensure_object(categories)
    else:
        values = ensure_object(values)
        categories = ensure_object(categories)

    (hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
    (_, _), cats = _get_data_algo(categories, _hashtables)
    t = hash_klass(len(cats))
    t.map_locations(cats)
    return coerce_indexer_dtype(t.lookup(vals), cats)
Example #4
Source File: categorical.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def _get_codes_for_values(values, categories):
    """
    utility routine to turn values into codes given the specified categories
    """

    from pandas.core.algorithms import _get_data_algo, _hashtables
    if not is_dtype_equal(values.dtype, categories.dtype):
        values = _ensure_object(values)
        categories = _ensure_object(categories)

    (hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
    (_, _), cats = _get_data_algo(categories, _hashtables)
    t = hash_klass(len(cats))
    t.map_locations(cats)
    return coerce_indexer_dtype(t.lookup(vals), cats)
Example #5
Source File: categorical.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def _get_codes_for_values(values, categories):
    """
    utility routine to turn values into codes given the specified categories
    """

    from pandas.core.algorithms import _get_data_algo, _hashtables
    if not is_dtype_equal(values.dtype, categories.dtype):
        values = _ensure_object(values)
        categories = _ensure_object(categories)

    (hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
    (_, _), cats = _get_data_algo(categories, _hashtables)
    t = hash_klass(len(cats))
    t.map_locations(cats)
    return coerce_indexer_dtype(t.lookup(vals), cats)